煮糖过程的建模与控制
摘要
煮糖工序是强非线性的工序。在这个过程中既有传热,又有传质,是一个复杂的化学和物理过程。从制糖工艺学中可知,在众多过程工艺参数中,母液的过饱和度对煮糖质量的影响最为显著,必须将这一参数控制在适当的范围内。
如果能够建立一个符合新理论的过程模型并进行仿真、控制,从而对设计一个适合的、性能良好、尽可能理想的结晶器,对优化煮糖工序的性能,以及控制蔗糖晶体的粒度分布,蔗糖产品的质量都是有重大意义的。本文针对当前糖厂生产现状,在总结先前研究成果的基础上,从蔗糖结晶的机理出发,结合当前蔗糖结晶动力学研究发展的新理论建立基于晶体生长机理的微分方程,以间歇式煮糖过程的物料平衡方程、晶体生长动力学方程以及矩平衡方程为基础,建立了基于与粒度有关的晶体生长理论的煮糖过程模型。本文采用工业生产中甲糖煮炼的初始条件进行模拟计算,并采用工业生产中甲糖煮炼的初始条件,对煮糖结晶过程进行传统的PID控制和非线性PID控制,从结果分析,所建立的模型具有较好的准确性,可以作为应用各种先进控制算法的基础。
Crystallization is one of the key steps in the cane sugar processing. And sugar cryatallization with strongly nonlinearity and nonstationarity is a complicated physicochemical process. It is the step that produces the final product which must be monitored very closely as the quality of the final product determines profit. Crystallization occurs by boiling a sugar solution until it becomes oversaturated and crystals grow. Care must be taken not to exceed a critical oversaturation to prevent nucleation of new cyrystals, as these greatly affect the quality of the final product. So oversaturation must be controlled well.Since the crystallization process is complex , a model is required to understand the effect of operating conditions on parameters such as growth rate and crystal size. What's more, the first and maybe the most important step in designing a perfect controller is to develop a model as accurate as possible, which is valid under a wide range of operating conditions.In this paper, a working model for the batch is developed and discussed. And the matlab coding for the working dynamic model of batch vacuum pan has been completed and tested. According to the control characteristic of sugar crystal process, a kind of nonlinear PID controller is designed. From the effect of a series of simulations, the nonlinear PID controller can efficiently achieve to control the oversaturation and help to design the actual auto-control system of sugar crystal process. From the results, we can see the model presented in this paper is validated.
如果能够建立一个符合新理论的过程模型并进行仿真、控制,从而对设计一个适合的、性能良好、尽可能理想的结晶器,对优化煮糖工序的性能,以及控制蔗糖晶体的粒度分布,蔗糖产品的质量都是有重大意义的。本文针对当前糖厂生产现状,在总结先前研究成果的基础上,从蔗糖结晶的机理出发,结合当前蔗糖结晶动力学研究发展的新理论建立基于晶体生长机理的微分方程,以间歇式煮糖过程的物料平衡方程、晶体生长动力学方程以及矩平衡方程为基础,建立了基于与粒度有关的晶体生长理论的煮糖过程模型。本文采用工业生产中甲糖煮炼的初始条件进行模拟计算,并采用工业生产中甲糖煮炼的初始条件,对煮糖结晶过程进行传统的PID控制和非线性PID控制,从结果分析,所建立的模型具有较好的准确性,可以作为应用各种先进控制算法的基础。
Crystallization is one of the key steps in the cane sugar processing. And sugar cryatallization with strongly nonlinearity and nonstationarity is a complicated physicochemical process. It is the step that produces the final product which must be monitored very closely as the quality of the final product determines profit. Crystallization occurs by boiling a sugar solution until it becomes oversaturated and crystals grow. Care must be taken not to exceed a critical oversaturation to prevent nucleation of new cyrystals, as these greatly affect the quality of the final product. So oversaturation must be controlled well.Since the crystallization process is complex , a model is required to understand the effect of operating conditions on parameters such as growth rate and crystal size. What's more, the first and maybe the most important step in designing a perfect controller is to develop a model as accurate as possible, which is valid under a wide range of operating conditions.In this paper, a working model for the batch is developed and discussed. And the matlab coding for the working dynamic model of batch vacuum pan has been completed and tested. According to the control characteristic of sugar crystal process, a kind of nonlinear PID controller is designed. From the effect of a series of simulations, the nonlinear PID controller can efficiently achieve to control the oversaturation and help to design the actual auto-control system of sugar crystal process. From the results, we can see the model presented in this paper is validated.
引文
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[5] 刘金琨,先进PID控制及其MATLAB仿真,电子工业出版社,2003
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[54] D.I.Wilson, P.L.Lee, E.T. White and R.B.Newell, Advanced control of a sugar crystallizer, Process Control Group, Department of Chemical Engineering , The University of Queensland (1991)
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[2] 广东省糖纸工业公司,煮糖结晶过程,轻工业出版社,1989
[3] 沈继红,数学建模,哈尔滨工程大学出版社,1996
[4] 何小阳,计算机监控技术,重庆大学出版社,2002
[5] 刘金琨,先进PID控制及其MATLAB仿真,电子工业出版社,2003
[6] 薛毅,数学建模基础,北京工业大学出版社,2004
[7] 王维平,朱一凡,华雪倩,离散事件系统建模与仿真,国防科技大学出版社,1996
[8] 王寅,化工过程混合建模问题研究,浙江大学博士学位论文,2000
[9] 王骥程,祝和运,化工过程控制工程,北京,化学工业出版社,1991
[10] 王之才,关于仿真理论的探讨,系统仿真学报,2001,12(6):604-608
[11] 陆经纬,延迟焦化过程计算机稳态建模研究,浙江大学硕士学位论文,2000。
[12] 方崇智,萧德云,系统辨识,北京,清华大学出版社,1988
[13] 丁绪淮,谈道,工业结晶,北京,化学工业出版社,1985
[14] 陈树功,现代制糖工艺理论,北京,轻工业出版社,1988
[15] 无锡轻工业学院,华南工业学院,甘蔗制糖工艺学,北京,轻工业出版社,1982
[16] 广东省糖纸食品工业公司,糖膏煮炼与助晶,北京,轻工业出版社,1977
[17] 许斯欣,陈维钧,林福兰,甘蔗制糖原理与技术第四分册—蔗糖结晶与成糖,北京,中国轻工业出版社,2001
[18] 黄福五,钟耀南,李扬训,甘蔗制糖机械设备,北京,中国轻工业出版社,1992
[19] 广东化工学院制糖教研组,甘蔗制糖技术(上、下)
[20] 李利军,孔红星,何云等,蔗汁中蔗糖含量的分光光度法测定,分析测试学报,2003.7
[21] 黄桂忠,蔗糖连续结晶的应用及其强化,甘蔗糖业,2001.1
[22] 秦贯丰,陈树功,欧阳小容,用红外光度法测量糖液过饱和度的研究,华南理工大学学报(自然科学版),1994.6
[23] 张喜梅,丘泰球,声场对蔗糖晶体生长的影响,中国甜菜糖业,1995.4
[24] 史英,胡立杰,蔗糖晶体生长机理的探讨,中国甜菜糖业,2002.3
[25] Joseph. B. Kuntz,蔗糖混浊度与色值的测定,中国甜菜糖业,1994.1
[26] 李琳,陈树功,物理场在蔗糖结晶过程中的影响,华南理工大学学报(自然科学版), 1994.6
[27] 李冰,李琳,蔡妙颜等,微波场中蔗糖晶体生长动力学的研究,中国甜菜糖业,1998.6
[28] 高平,朱玉龙,全晶种投种养晶法在煮糖中的应用,中国甜菜糖业,1995.5
[29] 郭继强,强制循环结晶罐糖膏煮制的研究,大连轻工业学院学报,1994.6
[30] F.雷格,H.威萨罗维,强制循环结晶罐的选择与计算,中国甜菜糖业,1996.2
[31] 林丹,罗建军,王胜春等,间歇结晶过程的分析,天津化工,2001.9
[32] 文绍纯,罗飞,莫鸿强,基于神经网络的甘蔗制糖结晶过程预测,甘蔗糖业,2000.6
[33] 闵亚光,陈树功,高大维,蔗糖溶液成核起晶点临界尺寸的研究,华南理工大学学报(自然科学版),1995.5
[34] 高大维,陈树功,李国基等,煮糖起晶制种新方法,华南理工大学轻化工所
[35] 李尔炫,煮糖起品技术的发展和进步,甘蔗糖业,1999.6
[36] 张继峰,王茹菊,蔗糖晶体生长机理探讨,中国甜菜糖业,2001.3
[37] 郭渭鸿,蔗糖工业结晶过程糖膏电导值的关联分析,福建糖业,1997.3
[38] 唐忠义,高浩业,王智海,微机在制糖工业上的应用,工农业新技术,1993.1
[39] 李琳,陈树功,蔗糖晶体在一定的流体力学条件下生长的研究,华南理工大学轻化工研究所
[40] Terry V Tahal, New Models for Sugar Vacuum Pans, The University of Queensland, 2000
[41] Benjamin J. McCoy, A population balance framework for nucleation, growth, and aggregation, Chemical Engineering Science 57 (2002) 2297-2285
[42] Richard D. Braatz, Advance control of crystallization of processes, Annual Reviews in Control 26 (2002) 87-99
[43] Hiroshi Takiyama, Masakuni Matsuoka, Design of seed crystal specifications for start-up operation of a continuous MSMPR crystallizer, Powder Technology 121 (2001) 99-105
[44] P. Lauret, H. Boyer, J. C. Gatina, Hybrid modelling of a sugar boiling process, Control Engineering Practice 8 (2000) 299-310
[45] A. Vega, F. Diez, J. M. Alvarez, Programmed cooling control of a batch crystallizer, Computers and Chemical Engineering (1995)
[46] F. Puel, G. Fevotte, J. P. Klein, Simulation and analysis of industrial crystallization processes through multidimensional population balance equations, Chemical Engineering Science 58 (2003) 3715-3727
[47] Gu Shan, Koichi Igarashi, Hideo Noda, Hiroshi Olshima, Production of large crystals with a narrow crystal size distribution by a novel WWDJ batch crystallizer, Chemical Engineering Journal 85 (2002) 161-167
[48] Serena H. Chung, David L. Ma, Richard D. Braatz, Optimal model-based experimental design in batch crstallization, Chemometrics and Intelligent Laboratory Systems 50 (2000) 83-90
[49] N. Semlali Aouragh Hassani, K. Saidi, T. Bounahmidi, Steady state modeling and simulation of an industrial sugar continuous crystallizer, Computers and Chemical Engineering 25 (2001)1351-1370
[50] E.T.Whi, D.L.Mackintosh, B.K.Butl, Modeling Growth Rate Dispersion(GRD)in Sugar Crystallision, Proc.Aust.Soc.Sugar Cane Technol
[51] Daviel, Ian, WilsonAdvancedControl of a Batch Raw Sugar Crystalliser Department of Chemical Engineering 1990
[52] E. T. White, A Simple Procedure to Analyse Size Distributions from An MSMPR with Growth Rate Dispersion, World Congress on Particle Technology Conference (2002)
[53] A.Gerstlauer, S.Motz, S.Mitrovic, Development, analysis and validation of population models for continuous and batch cyrstallizers, ELSEV1ER Chemical Engineering Science, 57(2002)
[54] D.I.Wilson, P.L.Lee, E.T. White and R.B.Newell, Advanced control of a sugar crystallizer, Process Control Group, Department of Chemical Engineering , The University of Queensland (1991)
[55] Helge Didriksen, Model based predictive control of a rotary dryer, Chemical Engineering Journal 86 (2002) 53-60
[56] M. Wulkow, A. Gerstlauer, U. niekenModeling and simulation of crystallization processes using parsivalChemical Engineering Science 50 (2001) 2575-2588
[57] M. Loffelmann, A. Mersmann, How to measure supersaturation?, Chemical Engineering Science 57 (2002) 4301-4310
[58] Doraiswami Ramkrishna, Alan W. Mahoney, Population balance modeling. Promise for the future, Chemical Engineering Science 57(2002) 595-606
[59] Klaus Borho, The miportance of population dynamics from the perspective of the chemical process industry, Chemical Engineering Science 57 (2002) 4257-4266
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